code: def test_fc_stack_input_size_mismatch_fails():
      first_layer_input_size = 10
      layers = [{"input_size": 2, "output_size": 4}, {"output_size": 8}]
  
      fc_stack = FCStack(
          first_layer_input_size=first_layer_input_size,
          layers=layers,
      ).to(DEVICE)
      input_tensor = torch.randn(
          BATCH_SIZE, first_layer_input_size, device=DEVICE
      )
  
      with pytest.raises(RuntimeError):
          fc_stack(input_tensor)
  
file_path: ludwig/tests/ludwig/modules/test_fully_connected_modules.py
imports: from typing import List, Optional
  import numpy
  import pytest
  import torch
  from ludwig.modules.fully_connected_modules import FCLayer, FCStack
  from ludwig.utils.misc_utils import set_random_seed
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 3 for calling a global function with example usage: test_fc_stack_input_size_mismatch_fails() without return types